MoodShaker / app.py
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import os
import gradio as gr
import json
import re
from datetime import datetime
import openai
import random
from html2image import Html2Image
user_db = {
os.environ["username"]: os.environ["password"],
}
music_files = [
"RPReplay_Final1712757356.mp3",
"RPReplay_Final1712801927.mp3",
"RPReplay_Final1712802362.mp3",
"RPReplay_Final1712802406.mp3",
"RPReplay_Final1712757356.mp3",
"RPReplay_Final1712802448.mp3",
"RPReplay_Final1712802599.mp3"
]
# Function to play background music
def play_music():
"""Returns the path to the music file and makes the audio player visible."""
music_path = random.choice(music_files)
return music_path, gr.update(visible=True)
# Main function to generate a cocktail recipe based on user preferences
def generate_cocktail(mood, sweetness, sour, savory, bitter, flavor_association, drinking_experience, soberness_level, allergies, additional_requests):
"""Generates a cocktail recipe using OpenAI's GPT-4 based on user input."""
client = openai.OpenAI(api_key=os.environ["API_TOKEN"])
instruction = "Please provide a cocktail recipe given the mood and preference of the user.\n\n"
user_prompt = f"Mood: {mood}\nTaste: Sweetness {sweetness}/10, Sour {sour}/10, Savory {savory}/10, Bitter {bitter}/10\nFlavor: {flavor_association}\nDrinking Experience: {drinking_experience}\nLevel of Soberness: {soberness_level}\nAllergies: {allergies}\nAdditional Requests: {additional_requests}\n\nMake sure to avoid all allergic ingredients.\n\n"
output_format = "Please strictly follow this output format:\n\nCocktail Name:[name]\nQuote:[one sentence quote related to the cocktail and the mood description]\nIngredients:[ingredient 1]\n[ingredient 2]\n...\nInstruction:1. [step 1]\n2. [step 2]\n...\nNotes:[notes]"
prompt = instruction + user_prompt + output_format
messages=[
{"role": "system", "content": "You are a helpful bartender assistant."},
{"role": "user", "content": prompt}
]
try:
response = client.chat.completions.create(
model="gpt-4-0125-preview",
messages=messages,
max_tokens=1024)
name, quote, ingredients, instruction, notes = extract_info(response.choices[0].message.content)
return format_cocktail_output(name, quote, ingredients, instruction, notes), True, True
except Exception as e:
return f'<p style="color: white; font-size: 20px;">{str(e)}</p>'
# Extract information from the response generated by OpenAI
def extract_info(output_text):
"""Extracts the cocktail recipe information from the response text."""
pattern = r"Cocktail Name:(.*?)Quote:(.*?)Ingredients:(.*?)Instruction:(.*?)Notes:(.*?)$"
match = re.search(pattern, output_text, re.DOTALL)
if match:
name = match.group(1).strip()
quote = match.group(2).strip()
ingredients = match.group(3).strip().replace('\n', '<br>')
instruction = match.group(4).strip().replace('\n', '<br>')
notes = match.group(5).strip()
return name, quote, ingredients, instruction, notes
else:
return None
# Format the cocktail recipe for display
def format_cocktail_output(name, quote, ingredients, instruction, notes):
"""Formats the cocktail recipe into HTML for display."""
html_output = f'''
<div style="text-align: center; font-family: 'Verdana', sans-serif; color: white;">
<h1 style="font-size: 48px; color: white;">{name}</h1>
<p style="font-size: 36px; margin-top: -15px; font-style: italic; color: white;">{quote}</p>
<p style="font-size: 20px; color: white;">
<strong style="color: white;">Ingredients:</strong><br>
{ingredients}<br>
<strong style="color: white;">Instruction:</strong><br>
{instruction}<br>
<strong style="color: white;">Notes:</strong><br>
{notes}<br>
</p>
</div>
'''
return html_output
def save_as_png(html_content):
"""Converts HTML content to PDF, encodes it in base64, and returns a download link."""
hti = Html2Image()
css = 'body {background: url("https://images.unsplash.com/photo-1514361726087-38371321b5cd?q=80&w=2370&auto=format&fit=crop&ixlib=rb-4.0.3&ixid=M3wxMjA3fDB8MHxwaG90by1wYWdlfHx8fGVufDB8fHx8fA%3D%3D");}'
# screenshot an HTML string (css is optional)
hti.screenshot(html_str=html_content, css_str=css, save_as="CocktailRecipe.png")
with open('style.css', 'r') as file:
css_styles = file.read()
# Creating the Gradio interface
with gr.Blocks(css=css_styles) as MoodShaker:
with gr.Row():
gr.HTML('''
<div style="text-align: center; margin: 0;">
<img src="https://huggingface.co/spaces/WhartonHackAIthon/MoodShaker/resolve/main/MoodShaker_Slogan.png" alt="MoodShaker Cocktail Generator" class="centered-image">
</div>
''')
with gr.Row():
mood = gr.Textbox(label="How are you feeling today?", elem_classes=["custom-input"])
flavor_association = gr.CheckboxGroup(label="Flavor", choices=["Fruity", "Herbal", "Spicy", "Floral", "Nutty", "Woody", "Earthy"], elem_classes=["custom-checkbox-group1"])
drinking_experience = gr.CheckboxGroup(label="Drinking Experience", choices=["Refreshing", "Warming", "Comforting", "Energizing", "Relaxing"], elem_classes=["custom-checkbox-group2"])
with gr.Row():
sweetness = gr.Slider(label="Sweetness", minimum=0, maximum=10, elem_id="slider-sweetness",elem_classes=["slider-sweetness"])
sour = gr.Slider(label="Sour", minimum=0, maximum=10, elem_id="slider-sour", elem_classes=["slider-sour"])
savory = gr.Slider(label="Savory", minimum=0, maximum=10, elem_id="slider-savory", elem_classes=["slider-savory"])
bitter = gr.Slider(label="Bitter", minimum=0, maximum=10, elem_id="slider-bitter", elem_classes=["slider-bitter"])
soberness_level = gr.Slider(label="Level of Soberness", minimum=0, maximum=10, value=10, elem_id="slider-soberness_level", elem_classes=["slider-soberness_level"])
with gr.Row():
allergies = gr.Textbox(label="Allergies", scale=6, elem_classes=["custom-input1"])
additional_requests = gr.Textbox(label="Anything else you would like to address", scale=6, elem_classes=["custom-input2"])
generate_button = gr.Button("Generate Your Cocktail Recipe", scale=3, elem_classes=["generate-button"])
clear_button = gr.Button("Clear", scale=1)
with gr.Row():
output_recipe = gr.HTML(label="Your Cocktail Recipe")
play_button = gr.Button("Play Music", visible=False, elem_classes=["generate-button"], scale=1) # Initially not visible
background_music = gr.Audio(label="Background Music", autoplay=True, visible=False, scale=4) # Initially not visible
pdf_download_link = gr.HTML(visible=False) # For displaying the PDF download link
with gr.Row():
save_png_button = gr.Button("Download Recipe as PNG", visible=False)
def on_generate_click(*args):
recipe, show_play_button, show_save_button = generate_cocktail(*args)
return recipe, gr.update(visible=show_play_button), gr.update(visible=show_save_button)
def reset():
return "", 0, 0, 0, 0, [], [], 10, "", "", "", gr.update(visible=False), gr.update(visible=False), gr.update(visible=False)
generate_button.click(
fn=on_generate_click,
inputs=[mood, sweetness, sour, savory, bitter, flavor_association, drinking_experience, soberness_level, allergies, additional_requests],
outputs=[output_recipe, play_button, save_png_button]
)
with gr.Row():
gr.Examples(examples=[["Celebratory", 7, 3, 1, 2, ["Fruity", "Floral"], ["Energizing"], 5, "Nuts", "No ice"],
["Relaxed", 4, 6, 0, 5, ["Herbal", "Woody"], ["Comforting"], 2, "", "Extra mint"],
["Adventurous", 5, 5, 5, 0, ["Spicy", "Earthy"], ["Refreshing"], 8, "Shellfish", "Make it a double"]],
inputs=[mood, sweetness, sour, savory, bitter, flavor_association, drinking_experience, soberness_level, allergies, additional_requests],
outputs=[output_recipe, play_button], fn=on_generate_click)
play_button.click(fn=play_music, inputs=[], outputs=[background_music, background_music])
save_png_button.click(fn=save_as_png, inputs=[output_recipe], outputs=[pdf_download_link])
clear_button.click(fn=reset, inputs=[], outputs=[mood, sweetness, sour, savory, bitter, flavor_association, drinking_experience, soberness_level, allergies, additional_requests, output_recipe, play_button, background_music, save_png_button])
if __name__ == "__main__":
MoodShaker.launch(#enable_queue=False,
# Creates an auth screen
auth=lambda u, p: user_db.get(u) == p,
auth_message="Welcome to MoodShaker! \nEnter a Username and Password"
).queue()